Abstract. Snow algal bloom is a common phenomenon on melting snowpacks in polar and alpine regions and can substantially increase snow melt rates due to the effect of albedo reduction on the snow surface. In order to reproduce algal growth on the snow surface using a numerical model, temporal changes in snow algal abundance were investigated on the Qaanaaq Glacier in north-western Greenland from June to August 2014. Snow algae first appeared at the study sites in late June, which was approximately 94h after air temperatures exceeded the melting point. Algal abundance increased exponentially after this appearance, but the increasing rate became slow after late July, and finally reached 3.5 × 107cellsm−2 in early August. We applied a logistic model to the algal growth curve and found that the algae could be reproduced with an initial cell concentration of 6.9 × 102cellsm−2, a growth rate of 0.42d−1, and a carrying capacity of 3.5 × 107cellsm−2 on this glacier. This model has the potential to simulate algal blooms from meteorological data sets and to evaluate their impact on the melting of seasonal snowpacks and glaciers.

Snow algal bloom can substantially increase melt rates of the snow due to the effect of albedo reduction on the snow surface. In this study, the temporal changes in algal abundance on the snowpacks of Greenland Glacier were studied in order to reproduce snow algal growth using a numerical model. Our study demonstrates that a simple numerical model could simulate the temporal variation in snow algal abundance on the glacier throughout the summer season.

Snow algal bloom can substantially increase melt rates of the snow due to the effect of albedo...